added back formula

.vscode/c_cpp_properties.json

@@ -0,0 +1,18 @@
+{
+  "configurations": [
+    {
+      "name": "macos-clang-x64",
+      "includePath": [
+        "${workspaceFolder}/**"
+      ],
+      "compilerPath": "/usr/bin/clang",
+      "cStandard": "${default}",
+      "cppStandard": "${default}",
+      "intelliSenseMode": "macos-clang-x64",
+      "compilerArgs": [
+        ""
+      ]
+    }
+  ],
+  "version": 4
+}

.vscode/launch.json

@@ -0,0 +1,13 @@
+{
+  "version": "0.2.0",
+  "configurations": [
+    {
+      "name": "C/C++ Runner: Debug Session",
+      "type": "lldb",
+      "request": "launch",
+      "args": [],
+      "cwd": "/Users/smailalijagic/Desktop/Universität/26FS/Advanced Systems Lab/team70",
+      "program": "/Users/smailalijagic/Desktop/Universität/26FS/Advanced Systems Lab/team70/build/Debug/outDebug"
+    }
+  ]
+}

.vscode/settings.json

@@ -0,0 +1,59 @@
+{
+  "C_Cpp_Runner.cCompilerPath": "clang",
+  "C_Cpp_Runner.cppCompilerPath": "clang++",
+  "C_Cpp_Runner.debuggerPath": "lldb",
+  "C_Cpp_Runner.cStandard": "",
+  "C_Cpp_Runner.cppStandard": "",
+  "C_Cpp_Runner.msvcBatchPath": "",
+  "C_Cpp_Runner.useMsvc": false,
+  "C_Cpp_Runner.warnings": [
+    "-Wall",
+    "-Wextra",
+    "-Wpedantic",
+    "-Wshadow",
+    "-Wformat=2",
+    "-Wcast-align",
+    "-Wconversion",
+    "-Wsign-conversion",
+    "-Wnull-dereference"
+  ],
+  "C_Cpp_Runner.msvcWarnings": [
+    "/W4",
+    "/permissive-",
+    "/w14242",
+    "/w14287",
+    "/w14296",
+    "/w14311",
+    "/w14826",
+    "/w44062",
+    "/w44242",
+    "/w14905",
+    "/w14906",
+    "/w14263",
+    "/w44265",
+    "/w14928"
+  ],
+  "C_Cpp_Runner.enableWarnings": true,
+  "C_Cpp_Runner.warningsAsError": false,
+  "C_Cpp_Runner.compilerArgs": [],
+  "C_Cpp_Runner.linkerArgs": [],
+  "C_Cpp_Runner.includePaths": [],
+  "C_Cpp_Runner.includeSearch": [
+    "*",
+    "**/*"
+  ],
+  "C_Cpp_Runner.excludeSearch": [
+    "**/build",
+    "**/build/**",
+    "**/.*",
+    "**/.*/**",
+    "**/.vscode",
+    "**/.vscode/**"
+  ],
+  "C_Cpp_Runner.useAddressSanitizer": false,
+  "C_Cpp_Runner.useUndefinedSanitizer": false,
+  "C_Cpp_Runner.useLeakSanitizer": false,
+  "C_Cpp_Runner.showCompilationTime": false,
+  "C_Cpp_Runner.useLinkTimeOptimization": false,
+  "C_Cpp_Runner.msvcSecureNoWarnings": false
+}

forces.cpp

@@ -18,15 +18,23 @@ double g(double v_max_alpha, double w_alpha_norm) {
 }
 
 // # 8 flops
+//
+// $\vec{F}_\alpha(\vec{v}_\alpha, v^0_\alpha \vec{e}_\alpha) \vec{e}_\alpha(t) = \frac{1}{\tau_\alpha}(v^0_\alpha \vec{e}_\alpha - \vec{v}_\alpha)$
+//
 void compute_acceleration_term(Pedestrian *p) {
   // # 2 flops
+  // $v_{\alpha}^{0}\vec{e}_{\alpha}$
   Vector2d desired_velocity = p->e * p->desired_v0;
+  // $\vec{v}_{\alpha}(t)$
   Vector2d actual_velocity = p->curr_vel;
   // # 6 flops = 4 ADDs, 2 DIVs
   p->f_i += (desired_velocity - actual_velocity) / tau_alpha;
 }
 
 // # 55(N - 1) = 55N - 55 flops
+//
+// $\sum_{\beta} \vec{F}_{\alpha\beta}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{\beta})$
+//
 void compute_repulsive_effects_from_pedestrians(Pedestrian *pedestrians, Pedestrian *p, int N) {
 
   for (int i = 0; i < N; i++) {
@@ -41,32 +49,50 @@ void compute_repulsive_effects_from_pedestrians(Pedestrian *pedestrians, Pedestr
     // }
 
     // # 2 ADDs
+    // $\vec{r}_{\alpha\beta}$
     Vector2d r_ab = p->curr_pos - pedestrians[i].curr_pos;
 
     // # 4 flops = 1 SQRT, 2 MULTs, 1 ADD
+    // $\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert$
     double r_ab_norm = r_ab.norm();
 
+    // $\vec{e}_{\beta}$
     Vector2d e_b = pedestrians[i].e;
 
     // # 2 MULTs
-    double s_b = pedestrians[i].desired_v0 * delta_t;
+    // $v_\beta \Delta t$
+    double s_b = pedestrians[i].curr_vel.norm() * delta_t;
 
     // # 4 flops = 2 ADDs, 2 MULTs
+    // $\vec{r}_{\alpha\beta} - \vec{v}_{\beta}\varDelta_{t}\vec{e}_{\beta}$
     Vector2d r_ab2 = r_ab - (e_b * s_b);
 
     // # 4 flops = 1 SQRT, 2 MULTs, 1 ADD
+    // $\Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert$
     double r_ab2_norm = r_ab2.norm();
 
     // # 7 flops = 1 SQRT, 3 ADDs, 2 MULTs, 1 DIV
+    //
+    // $(4):2b = \sqrt{(\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert + \Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert)^2 - (v_\beta \Delta t)^2}$
+    //
     double b = sqrt((r_ab_norm + r_ab2_norm) * (r_ab_norm + r_ab2_norm) - s_b * s_b) / 2;
 
     // # 12 flops = 6 DIVs, 3 ADDs, 3 MULTs
+    //
+    // $(7):\grad_{\vec{r}_{\alpha \beta}}b = \frac{(\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert + \Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert) (\frac{\vec{r}_{\alpha \beta}}{\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert} + \frac{\vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta}{\Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert})}{4b}$
+    //
     Vector2d b_grad = (r_ab / r_ab_norm + r_ab2 / r_ab2_norm) * (r_ab_norm + r_ab2_norm) / (4 * b);
 
     // # 6 flops = 3 MULTs, 2 DIVs, 1 EXP
+    //
+    // $(5):\vec{f}_{\alpha \beta}(\vec{r}_{\alpha \beta}) = \frac{V^0_{\alpha \beta}}{\sigma}e^{-b / \sigma} \grad_{\vec{r}_{\alpha \beta}}b$
+    //
     Vector2d f_ped = b_grad * ((V0_AB / SIGMA) * (exp(-b / SIGMA)));
 
     // # 14 flops: 9 MULTs, 4 ADDs, 1 SQRT
+    //
+    // $(11):\vec{F}_{\alpha\beta}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{\beta}) = w(\vec{e}_{\alpha}, -\vec{f}_{\alpha\beta})\vec{f}_{\alpha\beta}(\vec{r}_{\alpha} - \vec{r}_{\beta})$
+    //
     p->f_i += f_ped * w(p->e, f_ped * -1);
   }
 }
@@ -83,9 +109,13 @@ void compute_repulsive_effects_from_borders(Board &board, Pedestrian *p) {
     Obstacle obstacle = obstacles[i];
 
     // # 17 flops
+    // $\vec{r}_{\alpha B}$
     Vector2d r_aB = p->curr_pos - obstacle.find_nearest_obstacle_point(p->curr_pos);
 
     // # 17 flops = 2 DIVs, 1 SQRT, 2 MULTs, 1 ADD, 2 MULTs, 1 DIV, 2 MULTs, 1 EXP, 1 SQRT, 2 MULTs, 1 ADD, 1 DIV
+    //
+    // $\vec{F}_{\alpha B}(\vec{r}_{\alpha B}) = \frac{U^0_{\alpha B}}{R} e^{- \Arrowvert \vec{r}_{\alpha B} \Arrowvert / R} \frac{\vec{r}_{\alpha B}}{\Arrowvert \vec{r}_{\alpha B} \Arrowvert}$
+    //
     Vector2d f_obst = (r_aB / r_aB.norm()) * (U0_AB / R) * std::exp(-r_aB.norm() / R);
 
     // # 2 ADDs
@@ -95,6 +125,9 @@ void compute_repulsive_effects_from_borders(Board &board, Pedestrian *p) {
     // However, the formulas above for attractive and repulsive effects only hold for situations that are perceived in the desired direction e_alpha(t) of motion.
     // I assumed that with formulas above its also meant for equation 8 (even though not explicitly mentioned their)
     // # 14 flops: 9 MULTs, 4 ADDS, 1 SQRT
+    // 
+    // $(12):\vec{F}_{\alpha B}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{ B}) = w(\vec{e}_{\alpha}, -\vec{F}_{\alpha B})\vec{F}_{\alpha B}(\vec{r}_{\alpha} - \vec{r}_{ B})$
+    //
     p->f_i += f_obst * w(p->e, f_obst * -1);
   }
 }

forces.hpp

@@ -3,25 +3,34 @@
 #include "pedestrian.hpp"
 #include <cmath>
 
+// $\tau_{\alpha}$
 const double tau_alpha = 0.5;
 
+// $V^0_{\alpha \beta}$
 const double V0_AB = 2.1;
 
+// $\sigma$
 const double SIGMA = 0.3;
 
+// $U^0_{\alpha B}$
 const double U0_AB = 10.0;
 
+// $R$
 const double R = 0.2;
 
+// $c$
 const double c = 0.5;
 
+// $\varphi$
 const double phi = 100.0 / 180.0 * M_PI;
 
 const double cos_phi = cos(phi);
 
+// $\varDelta_{t}$
+// step size = 0.2 seconds
 const double delta_t = 2;
 
-const double dt = 0.01;
+const double dt = 0.001;
 
 // # Optional (forces.cpp: compute_repulsive_effects_from_pedestrians)
 // const double DISTANCE = 2.0;

main.cpp

@@ -67,7 +67,7 @@ int main(int argc, const char *argv[]) {
   int n_iter = atoi(argv[2]);
 
   // Logic to get/dump the simulation data
-  const int dump_interval = 5; // dump every 5 iterations -> 20 fps (since dt = 0.01)
+  const int dump_interval = 50; // dump every 5 iterations -> 20 fps (since dt = 0.01)
   const char *dump_path = (argc >= 4) ? argv[3] : nullptr;
 
   std::vector<std::tuple<int, int, double, double, int>> samples; // t, id, x, y, color
@@ -89,12 +89,21 @@ int main(int argc, const char *argv[]) {
       p.f_i.reset();
 
       // # 8 flops
+      //
+      // $\vec{F}_\alpha(\vec{v}_\alpha, v^0_\alpha \vec{e}_\alpha) \vec{e}_\alpha(t) = \frac{1}{\tau_\alpha}(v^0_\alpha \vec{e}_\alpha - \vec{v}_\alpha)$
+      //
       compute_acceleration_term(&p);
 
       // # 55N - 55 flops
+      //
+      // $\sum_{\beta} \vec{F}_{\alpha\beta}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{\beta})$
+      //
       compute_repulsive_effects_from_pedestrians(pedestrians, &p, n_p);
 
       // # 192 flops
+      //
+      // $\sum_{B} \vec{F}_{\alpha B}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{B})$
+      //
       compute_repulsive_effects_from_borders(board, &p);
     }
     // Pass2: integrate the forces and update the current state
@@ -109,6 +118,9 @@ int main(int argc, const char *argv[]) {
       p.curr_vel = p.w * g(p.v_max, p.w.norm());
 
       // # 4 flops = 2 ADDs, 2 MULTs
+      //
+      // $\vec{r}_i^{t+1} += \vec{r}^t_i + v^t_idt$
+      //
       p.curr_pos = p.curr_pos + p.curr_vel * dt;
 
       // how to handle if a pedestrian reached the end of our simulation/end of the hallway

pedestrian.hpp

@@ -7,13 +7,21 @@ enum Color { BLACK, WHITE };
 
 struct Pedestrian {
   Color color;
+  // $\vec{v}_{\alpha}(t)$
   Vector2d curr_vel; // v_alpha  (actual, ≤ v_max)
+  // $\vec{w}_{\alpha}$
   Vector2d w;        // w_alpha  (preferred, integrates force)
+  // $\vec{r}_\alpha(t)$
   Vector2d curr_pos;
+  // $\vec{e}_{\alpha}(t)$
   Vector2d e;
+  // $v_{\alpha}^{max} = 1.3 v^{0}_{\alpha}$
   double v_max;
+  // $v_\alpha^0$
   double desired_v0;
+  // $\vec{r}^0_\alpha$
   Vector2d destination;
+  // social force
   Vector2d f_i;
 
   Pedestrian() : color(WHITE), curr_vel(0.0, 0.0), w(0.0, 0.0), curr_pos(0.0, 0.0), e(0.0, 0.0), v_max(0.0), desired_v0(0.0), destination(0.0, 0.0), f_i(0.0, 0.0) {}